Dawning of the age of AI

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One of the biggest strategy considerations for business leaders today is how artificial intelligence (AI) will impact their industry, the economy—and hence their profitability— in the future. They have reason to be optimistic. Expert projections promise significant economic gains from the use of AI. One consultancy, PwC, estimates AI developments will add $15.7 trillion to the global economy by 2030. Another, Accenture, looks further ahead, and projects the economic value added by AI in 2035 to be $8.3 trillion in the US alone.

Some industries, such as financial services, health and life sciences, and automotive, where AI has already been deployed to good effect in several areas, are likely to be the first to generate demonstrable benefits from its use in the coming years.

Intelligent change

In financial services, banks, wealth managers and insurers will build a wider variety of innovative, algorithm-driven customer services, but will also use AI to greater effect in the back office, automating payments, fraud detection, risk management and other critical processes. In healthcare, Accenture believes that AI use will generate $150 billion in annual savings for US health organisations by 2026, with applications in surgery, nursing and administrative workflow the biggest contributors. And among Automotive producers—20% of whom have fully implemented multiple AI use cases already, according to the Boston Consulting Group (BCG)—AI will bring autonomous vehicles to market and deliver ever more intelligent in-car services.

In manufacturing, AI will come into use well beyond the automotive and semiconductor industries. Heavy equipment, consumer goods and other discrete manufacturers, as well as those in some process industries, will leverage AI to improve asset productivity, boost product quality, increase yield and optimise their supply chains. In China, for example, a survey conducted recently by Forrester for leading global technology company, Huawei, found that 51% of large manufacturers plan to boost investments in production line automation, and 45% plan to increase spending on AI in inventory forecasting. The same share of respondents reported plans to use AI to help improve quality control.

The future benefits

The long-term impacts of AI on the economy and society may be difficult to predict, but it does not require a crystal ball to see the benefits it will generate in the next 5-10 years. Elements of AI, such as machine learning, are already being used to good effect in all of these sectors in several ways. Banks use chatbots to address customer queries and more generally to improve customer service. Insurers now use algorithms to underwrite automotive and health insurance premiums. AI is widely used by hospitals and medical science labs to help doctors diagnose illnesses and prescribe appropriate treatment. Semiconductor manufacturers are using AI to take automation to higher levels. Auto producers are leveraging Internet of Things (IoT) sensors and AI algorithms to deliver real-time traffic, safety and other information to cars.

To perform its magic, AI relies on two commodities: computing power and data. The growth of cloud computing in the past half-decade has provided the mass of server capacity that many AI applications need for their number-crunching. Different sorts of power will also soon be available. One is represented by “edge computing”, which brings greater power to the outer edge of networks or devices themselves, so that the latter can perform analysis and take decisions that are time-sensitive.

Computer chips are also coming to market that are specific to the needs of AI. “The new AI chips coming into use closely mimic the neuron process inside the brain, much more so than the all-purpose chips that AI has relied on until now,” says Andrei Kirilenko, Director of the Centre for Global Finance and Technology at Imperial College London. They will make more efficient use of the available computing power, in the cloud and within devices. The result is likely to be greater overall precision of AI applications—and the decisions they make—and a reduced cost of hardware carrying AI chips.

AI’s capabilities will also grow with improvements in “machine vision”, which allows software to inspect and evaluate images of static or moving objects. Such advances will widen the variety of data sources that algorithms can reliably analyse. The technology will be used not only in autonomous vehicles and transportation systems but also on the factory floor. There manufacturers will use it in conjunction with IoT sensors to enable predictive maintenance of capital-intensive equipment, thus avoiding expensive downtime. “AI-enhanced predictive maintenance will be a game-changer for parts of the industrial sector,” says Harald Bauer, a Senior Partner with consulting firm McKinsey, based in Frankfurt, Germany.

Related applications will emerge in the healthcare sector, in the form of advanced medical imaging technologies. AI-based imaging will be used, for example, to screen different forms of cancer. The aforementioned Forrester survey found that 33% of large Chinese health organisations intend to adopt such smart imaging technologies in the next 3 years.

Bringing AI to scale

As bright as AI’s potential is, organisations will not realise it unless they can scale its applications across a much greater swathe of their operations. In order to do this address several challenges need to be addressed. One of the most pressing of these is strategy development. In a survey conducted by the Boston Consulting Group, a consultant, 87% of executives said their firms intend to implement AI in their operations with the next three years, but only 28% have devised a roadmap for implementation. AI’s benefits will come not from technology deployment but from the follow-on adaptation—or in some cases wholesale re-thinking—of production, back-office and front-office processes. Such endeavours require detailed planning.

Companies also need to invest in and develop expertise. Few organisations believe they have adequate internal knowledge today to develop and work with AI-based applications. Over one-third (36%) of respondents to a recent Economist Intelligence Unit survey cite a lack of requisite people or tools as a major risk of adopting AI, second only to its costs. Expertise gaps will not be filled overnight, but companies can start to address them by creating an inventory of existing skills and identifying missing skill sets.

Data fragmentation also needs to be eliminated. Many AI algorithms need to crunch large amounts of data to be effective. Organisations across industries generate data today in abundance, but far from all of it can be used by AI software as it resides in disparate repositories that are difficult to integrate and aggregate. Greater interoperability of data sets and systems that exist within organisations is required, as well as those that link organisations on external platforms. AI will bloom when the use of open, standardised data sources is the norm.

Competitive edge

Importantly, AI needs to become more transparent. Consumers as well as regulators will demand that companies that provide AI-based products and services are able to see into the “black box” where algorithms make decisions. Brian Kalis, Managing Director of Digital Health with Accenture, says “explainable AI” in healthcare is critical but elusive: “As a clinician or administrator, you need to be able to show and explain the rationale for a machine-based decision, especially if it impacts people’s lives,” he says. “This is a major challenge with advanced AI algorithms.”

The challenges notwithstanding, companies must press ahead to plan for AI’s implementation in their businesses. It has moved well beyond the science labs, and is already a competitive tool for a handful of firms that are developing new services and even business models based upon it. There remain unknowns about how AI will develop in the longer term, and certainly business risks as attendant in any major technology undertaking. The bigger risk, however, is remaining on the sidelines, as the AI future is now.

HUAWEI CONNECT 2018 – “Activate Intelligence” – will be held at the Shanghai World Expo Exhibition and Convention Center and Expo Center from October 10 to 12.

This year’s HUAWEI CONNECT conference is designed to help all businesses and organizations step over the threshold and stake their claim in the intelligent world. You will be joined by the best minds in the industry – including global ICT leaders, industry experts, and ecosystem partners – to chart the way forward and explore new opportunities.

Huawei is a leading global provider of information and communications technology (ICT) infrastructure and smart devices. With integrated solutions across four key domains – telecom networks, IT, smart devices, and cloud services – we are committed to bringing digital to every person, home and organization for a fully connected, intelligent world. Huawei’s end-to-end portfolio of products, solutions and services are both competitive and secure. Through open collaboration with ecosystem partners, we create lasting value for our customers, working to empower people, enrich home life, and inspire innovation in organizations of all shapes and sizes. At Huawei, innovation focuses on customer needs. We invest heavily in basic research, concentrating on technological breakthroughs that drive the world forward. We have more than 180,000 employees, and we operate in more than 170 countries and regions. Founded in 1987, Huawei is a private company fully owned by its employees.

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